code: def test_input_types(self, x_dtype, clip_norm_dtype):
      # Tests combinations of input dtypes.
      stage = clipping.ClipByNormEncodingStage(
          tf.constant(1.0, clip_norm_dtype)
      )
      x = tf.constant([1.0, 1.0, 1.0, 1.0], dtype=x_dtype)
      encode_params, decode_params = stage.get_params()
      encoded_x, decoded_x = self.encode_decode_x(
          stage, x, encode_params, decode_params
      )
      test_data = test_utils.TestData(x, encoded_x, decoded_x)
      test_data = self.evaluate_test_data(test_data)
  
      self.assertAllEqual([1.0, 1.0, 1.0, 1.0], test_data.x)
      # The decoded values should have norm 1.
      self.assertAllClose([0.5, 0.5, 0.5, 0.5], test_data.decoded_x)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import itertools
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow_model_optimization.python.core.internal.tensor_encoding.stages.research import clipping
  from tensorflow_model_optimization.python.core.internal.tensor_encoding.testing import test_utils
label_desc: Use image node_id 8 for calling the ClipByNormEncodingStageTest obj's underlying member method code with example usage: obj.test_input_types(x_dtype, clip_norm_dtype) without return types